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SMT models . However , confusion
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brings high computational complexity
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E09-3009 |
According to the adopted semantic
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model , each semantic edge type
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Figure 1 ( c ) . The confusion
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is largely influenced by the
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P11-1125 |
parsing errors such as the confusion
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influenced by alignment errors
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P13-1107 |
in tweets to enrich information
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. After applying the same annotation
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P09-1106 |
hy - pothesis . 3 ) Confusion
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: to build a confusion network
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against the efficiency of the
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. 4.2 Network Construction In
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dominated by the word confusion
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and parsing . Also , both the
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N06-1062 |
Turkish involves a static decoding
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and optimization resulting in
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W06-1662 |
and sentence ordering . Sentence
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Sentence classification Summary
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into Weibo tweets for information
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, and extract a new set of semantic
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translation edits . TER-based confusion
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and system combination has demonstrated
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in the next section . Confusion
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: confusion network is built
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described in Section 3.4 . 3.1
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We construct a network where
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been explored pre - viously . 2
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The syntactic and semantic DSNs
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described in Section 3.4 . 3.1
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We construct a network where
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one-to-one alignment for confusion
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. In the first stage , we count
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i.e. , s1 and s2 , we adopted the
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method that we introduced in
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tricks for clear and efficient
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and common pitfalls to avoid
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approach . 2 Wikipedia-based Semantic
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Wikipedia1 is a free online encyclopedia
|